Create multiple columns in pandas aggregation function

Question

I'd like to create multiple columns while resampling a pandas DataFrame like the built-in ohlc method.

def mhl(data):
    return pandas.Series([np.mean(data),np.max(data),np.min(data)],index = ['mean','high','low'])

ts.resample('30Min',how=mhl)

Dies with

Exception: Must produce aggregated value

Any suggestions? Thanks!

Answer 1

You can pass a dictionary of functions to the resample method:

In [35]: ts
Out[35]:
2013-01-01 00:00:00     0
2013-01-01 00:15:00     1
2013-01-01 00:30:00     2
2013-01-01 00:45:00     3
2013-01-01 01:00:00     4
2013-01-01 01:15:00     5
...
2013-01-01 23:00:00    92
2013-01-01 23:15:00    93
2013-01-01 23:30:00    94
2013-01-01 23:45:00    95
2013-01-02 00:00:00    96
Freq: 15T, Length: 97

Create a dictionary of functions:

mhl = {'m':np.mean, 'h':np.max, 'l':np.min}

Pass the dictionary to the how parameter of resample:

In [36]: ts.resample("30Min", how=mhl)
Out[36]:
                      h     m   l
2013-01-01 00:00:00   1   0.5   0
2013-01-01 00:30:00   3   2.5   2
2013-01-01 01:00:00   5   4.5   4
2013-01-01 01:30:00   7   6.5   6
2013-01-01 02:00:00   9   8.5   8
2013-01-01 02:30:00  11  10.5  10
2013-01-01 03:00:00  13  12.5  12
2013-01-01 03:30:00  15  14.5  14